Skip to main content
SpringerLink
Log in

Using Machine Learning to Help Students with Learning Disabilities Learn

  • Conference paper
  • First Online:
Sustainable Communication Networks and Application (ICSCN 2019)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 39))

  • 1095 Accesses

Abstract

The concept behind this learning modal is to connect education with technology to meet the different needs of each student. The main aim of personalized learning is to help students with disabilities.

Students with a disability often need subject matter presented through different methods, therefore it is imperative that these technological advances benefit all students with different learning styles. Machine Learning opens up new ways to help students with disabilities. Children with autism which is a neurological disorder need a personalized development system for their daily activities. Technology can play a substantial part.

The system includes 4 parts: (i) To predict the learning level of the user. (ii) Generating multimodal learning materials using web mining. (iii) User preferences are associated with the result. (iv) Personalized contents for users delineated with an intelligent interface.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Wagley, A., Akhter, P., Bhuiyan, M., Dahal, K., Hossain, A.: Web mining to generate multimodal learning materials for children with special needs. In: The 8th International Conference on Software, Knowledge, Intelligent Management and Applications, SKIMA 20I4, Dhaka (2014)

    Google Scholar 

  2. Pretschner, A., Gauch, S.: Ontology based personalized search. In: 1999 Proceedings of the 11th IEEE International Conference at Tools with Artificial Intelligence, Chicago, IL (1999)

    Google Scholar 

  3. Pretschner, A., Gauch, S.: Personalized search based on user search histories. In: Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence (2005)

    Google Scholar 

  4. Bhuiyan, M., Miraz, M.H., Banik, L.: Automated generation of learning materials for children with special needs in converged platforms using android. In: The 2nd International Symposium on Advanced and Applied Convergence (ISAAC 2014) (2014)

    Google Scholar 

  5. Shah, M., Shah, M., Shirke, A., Deulkar, K.: Providing personalized study material for learning disability using machine learning. Int. J. Res. Sci. Eng. (2017). e-ISSN: 2394–8299 Special Issue 7-ICEMTE March 2017

    Google Scholar 

  6. Mythili, M.S., Shanavas, A.R.M.: A novel approach to predict the learning skills of autistic children using SVM and decision tree. (UCSIT) Int. J. Comput. Sci. Inf. Technol. (2014)

    Google Scholar 

  7. Hutchinson, H., Bederson, B.: Interface design for children’s searching and browsing. U. of MDHCIL Technical report, HCIL-2005–25 (2005)

    Google Scholar 

  8. Hutchinson, H.: Children’s interface design for hierarchical search and browse. ACM SIGCAPH Comput. Phys. Handicap. 75, 11–12 (2003)

    Article  Google Scholar 

  9. Marsh, J.: Young children’s play in online virtual worlds. J. Early Child. Res. 7(3), 1–17 (2010)

    Google Scholar 

  10. Marsh, J.: Young children’s literacy practices in a virtual world: establishing an online interaction order. Read. Res. Q. 46(2), 101–118 (2011)

    Article  Google Scholar 

  11. Few, S.: Data visualization for human perception (2013). http://www.interactiondesign.org/encyclopedia/data_visualization_for_human_perception.html

  12. Marsh, J.: The techno-litaracy practices of young children. J. Early Child. Res. 2(1), 52–66 (2004)

    Article  MathSciNet  Google Scholar 

  13. Standen, P.J., Brown, D.J., Cromby, J.J.: The effective use of virtual environments in the education and rehabilitation of students with intellectual disabilities. British Journal of Educational Technology 32(3), 289–299 (2001)

    Article  Google Scholar 

  14. Attardi, G., Gulli, A., Sebastiani, F.: Automatic Web page categorization by link and context analysis. In: Proceedings of THAI, vol. 99, no. 99, pp. 105–119 (1999)

    Google Scholar 

  15. Kim, Y., Nam, T.: An efficient text filter for adult web documents. In: The 8th International Conference on Advanced Communication Technology. ICACT 2006, vol. 1, pp. 3-pp. IEEE, February 2006

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Engineering, St. Francis Institute of Technology, Mumbai, India

    Francis Dcruz, Vijitashw Tiwari & Mayur Soni

Authors
  1. Francis Dcruz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vijitashw Tiwari
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mayur Soni
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Francis Dcruz .

Editor information

Editors and Affiliations

  1. Surya Engineering College, Kathirampatti, Tamil Nadu, India

    P. Karrupusamy

  2. Department of Electrical Engineering, Da-Yeh University, Changhua, Taiwan

    Joy Chen

  3. Department of Computer Science, Kennesaw State University, Kennesaw, GA, USA

    Yong Shi

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Dcruz, F., Tiwari, V., Soni, M. (2020). Using Machine Learning to Help Students with Learning Disabilities Learn. In: Karrupusamy, P., Chen, J., Shi, Y. (eds) Sustainable Communication Networks and Application. ICSCN 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 39. Springer, Cham. https://doi.org/10.1007/978-3-030-34515-0_27

Download citation

Publish with us

Policies and ethics

Search

Navigation